| import json |
| from PIL import Image |
| import os |
|
|
|
|
| def convert_data(): |
| try: |
| |
| json_path = '/home1/gmh/InternVL-main/with_llm_confidence.json' |
| with open(json_path, 'r', encoding='utf-8') as f: |
| data = json.load(f) |
|
|
| base_dir = '/home1/gmh/profused_benchmark/dataset' |
| converted_data = [] |
| failed_images = [] |
| possible_extensions = ['.jpg', '.jpeg', '.png', '.bmp'] |
|
|
| for index, sample in enumerate(data['data']): |
| original_data=sample["origin_data"] |
| llm_confidence=original_data['llm_confidence'] |
| if llm_confidence<0.9: |
| continue |
| extend_data = sample['extend_data_1'] |
| image_count = extend_data['image_count'] |
| result = { |
| "id": index |
| } |
|
|
| |
| image_data = extend_data['image'] |
| if isinstance(image_data, str): |
| |
| image_path = image_data |
| elif isinstance(image_data, list) and image_data: |
| |
| image_path = image_data[0] |
| else: |
| |
| print(f"样本 {index} image 格式错误: {image_data}") |
| failed_images.append(str(image_data)) |
| result["image"] = str(image_data) |
| result["width"] = 897 |
| result["height"] = 1152 |
| image_tags = "\n".join(["<image>"] * image_count) |
| result["conversations"] = [ |
| { |
| "from": "human", |
| "value": f"{image_tags}\n{extend_data['question']}" |
| }, |
| { |
| "from": "gpt", |
| "value": extend_data['program_answer'] |
| } |
| ] |
| converted_data.append(result) |
| continue |
|
|
| |
| result["image"] = image_path |
|
|
| if image_count == 1: |
| absolute_image_path = os.path.join(base_dir, image_path) |
| print(f"样本 {index}, 图片路径: {image_path}, 绝对路径: {absolute_image_path}") |
|
|
| try: |
| |
| target_path = absolute_image_path |
| if not os.path.exists(absolute_image_path): |
| |
| for ext in possible_extensions: |
| temp_path = absolute_image_path + ext |
| if os.path.exists(temp_path): |
| target_path = temp_path |
| print(f"找到文件: {target_path}") |
| break |
| else: |
| print(f"文件不存在: {absolute_image_path} (也尝试了后缀)") |
| failed_images.append(image_path) |
| result["width"] = 897 |
| result["height"] = 1152 |
| image_tags = "\n".join(["<image>"] * image_count) |
| result["conversations"] = [ |
| { |
| "from": "human", |
| "value": f"{image_tags}\n{extend_data['question']}" |
| }, |
| { |
| "from": "gpt", |
| "value": extend_data['program_answer'] |
| } |
| ] |
| converted_data.append(result) |
| continue |
|
|
| |
| img = Image.open(target_path) |
| img.verify() |
| img = Image.open(target_path) |
| width, height = img.size |
| print(f"图片尺寸: {width}x{height}") |
| result["width"] = width |
| result["height"] = height |
| except Exception as e: |
| print(f"样本 {index} 读取图片 {image_path} 失败: {e}") |
| failed_images.append(image_path) |
| result["width"] = 897 |
| result["height"] = 1152 |
| else: |
| result["image"] = image_data |
| result["width_list"] = [240] * image_count |
| result["height_list"] = [23] * image_count |
|
|
| image_tags = "\n".join(["<image>"] * image_count) |
| result["conversations"] = [ |
| { |
| "from": "human", |
| "value": f"{image_tags}\n{extend_data['question']}" |
| }, |
| { |
| "from": "gpt", |
| "value": extend_data['program_answer'] |
| } |
| ] |
| converted_data.append(result) |
|
|
| if failed_images: |
| print(f"以下图片加载失败: {failed_images}") |
| return converted_data |
|
|
| except FileNotFoundError: |
| print(f"错误: 未找到 JSON 文件 {json_path}") |
| except json.JSONDecodeError: |
| print("错误: JSON 文件解析失败") |
| except Exception as e: |
| print(f"发生未知错误: {e}") |
| return [] |
|
|
|
|
| if __name__ == "__main__": |
| converted = convert_data() |
| if converted: |
| output_file_path = '/home1/gmh/InternVL-main/aaa1.jsonl' |
| with open(output_file_path, 'w', encoding='utf-8') as output_file: |
| for item in converted: |
| output_file.write(json.dumps(item, ensure_ascii=False) + '\n') |
| print(f"转换完成，输出保存至: {output_file_path}") |
| else: |
| print("转换失败，未生成输出文件") |
